Investigating Candida glabrata Urinary Tract Infections (UTIs) in Mice Using Bioluminescence Imaging.

Urinary tract infections (UTIs) are quite common and mainly caused by bacteria such as Escherichia coli. However, when patients have urinary catheters, fungal infections comprise up to 15% of these types of infections. Moreover, fungal UTIs have a high mortality, due to rapid spreading of the fungi to the kidneys. Most fungal UTIs are caused by Candida species, among which Candida albicans and Candida glabrata are the most common. C. glabrata is an opportunistic pathogenic yeast, phylogenetically quite close to Saccharomyces cerevisiae. Even though it is commonly isolated from the urinary tract and rapidly acquires resistance to antifungals, its pathogenesis has not been studied extensively in vivo. In vivo studies require high numbers of animals, which can be overcome by the use of non-invasive imaging tools. One such tool, bioluminescence imaging, has been used successfully to study different types of C. albicans infections. For C. glabrata, only biofilms on subcutaneously implanted catheters have been imaged using this tool. In this work, we investigated the progression of C. glabrata UTIs from the bladder to the kidneys and the spleen. Furthermore, we optimized expression of a red-shifted firefly luciferase in C. glabrata for in vivo use. We propose the first animal model using bioluminescence imaging to visualize C. glabrata in mouse tissues. Additionally, this UTI model can be used to monitor antifungal activity in vivo over time

Hijacking Transposable Elements for Saturation Mutagenesis in Fungi.

Transposable elements are present in almost all known genomes, these endogenous transposons have recently been referred to as the mobilome. They are now increasingly used in research in order to make extensive mutant libraries in different organisms. Fungi are an essential part of our lives on earth, they influence the availability of our food and they live inside our own bodies both as commensals and pathogenic organisms. Only few fungal species have been studied extensively, mainly due to the lack of appropriate molecular genetic tools. The use of transposon insertion libraries can however help to rapidly advance our knowledge of (conditional) essential genes, compensatory mutations and drug target identification in fungi. Here we give an overview of some recent developments in the use of different transposons for saturation mutagenesis in different fungi

Nitrogen and water use efficiency under rain-fed potato agriculture: an experimental study

status: publishe

Assessing the potato yield gap in the Peruvian Central Andes

The Peruvian Central Andes is a highly important area for potato production. Assessing the potato yield gap and the potential yield is an essential step towards sustainable crop intensification. Fifty-eight smallholder potato farmer's plots in total were monitored at field level during the 2005–2008 and 2010–2015 rainy cropping seasons. All the main crop management inputs were registered. Three field experiments (on-farm trials) established during the 2014–2017 rainy cropping seasons were used to calibrate (2014–2016) and validate (2016–2017) the SUBSTOR-potato model under potential conditions. Potential potato yield (Yp) was estimated for each individual field pilot plot (in kg ha−1) based on the calibrated and validated crop model. Yield gaps (Yg) were calculated as the difference between Yp and farmers' actual yield (Ya). A classification tree-based model predicting the potato gap quantiles was used to elucidate the main biophysical and crop management components inducing Yg. Performance of the SUBSTOR-potato model showed a close agreement of simulated crop biomass, tuber yield, and N-uptake (i.e. N-demand) with the measured data under potential conditions. Redefined index of agreement were 0.84 and 0.80 while the associated mean square error were 2232 and 916 kg tuber dry weight (DW) ha−1 for the calibration and validation, respectively. The mean farmers' actual DW yield was 7118 kg ha−1, however, a high variability due to heterogeneous biophysical conditions and crop management was found (from 710 to 18,885 kg DW ha−1). The potato Yg ranged from 0.1 to 95.8% of the potential yield (x¯ = 42.1%, x~ = 46.0%, σx = 28.14% and CV = 0.67), hence there is an important difference that needs to be reduced. The classification tree analysis showed that inorganic N is the main yield explaining factor. While large yield gaps (Fourth quantile) are induced by low Inorganic N (< 88 kg ha−1) and scarce Human Labour energy (< 4196 MJ ha−1), small yield gap (First quantile) is mainly attributed to high N-inputs (≥ 139 kg ha−1 inorganic and ≥ 154 kg ha−1 organic). Third and Second quantiles (mid potato yield gaps) were characterized by more intricate nutrient input use, being difficult to classify; the Third quantile was partially explained by Inorganic N (< 139 kg ha−1), while part of the Second quantile by Extractable soil phosphorus (< 7.3 mg kg−1) and Inorganic N (< 139 kg ha−1). This classification can be helpful to diagnose the main site-specific crop management and biophysical recommendations towards closing the potato yield gap. The analysis suggests that there is opportunity to enhance potato actual yields in the study zone. More rational amount of inputs together with best management practices might improve potato productivities. However, sustainable potato intensification should be complemented with the expected quantification of environmental burdens under the local socio-economic constraints.The Peruvian Central Andes is a highly important area for potato production. Assessing the potato yield gap and the potential yield is an essential step towards sustainable crop intensification. Fifty-eight smallholder potato farmer's plots in total were monitored at field level during the 2005–2008 and 2010–2015 rainy cropping seasons. All the main crop management inputs were registered. Three field experiments (on-farm trials) established during the 2014–2017 rainy cropping seasons were used to calibrate (2014–2016) and validate (2016–2017) the SUBSTOR-potato model under potential conditions. Potential potato yield (Yp) was estimated for each individual field pilot plot (in kg ha−1) based on the calibrated and validated crop model. Yield gaps (Yg) were calculated as the difference between Yp and farmers' actual yield (Ya). A classification tree-based model predicting the potato gap quantiles was used to elucidate the main biophysical and crop management components inducing Yg. Performance of the SUBSTOR-potato model showed a close agreement of simulated crop biomass, tuber yield, and N-uptake (i.e. N-demand) with the measured data under potential conditions. Redefined index of agreement were 0.84 and 0.80 while the associated mean square error were 2232 and 916 kg tuber dry weight (DW) ha−1 for the calibration and validation, respectively. The mean farmers' actual DW yield was 7118 kg ha−1, however, a high variability due to heterogeneous biophysical conditions and crop management was found (from 710 to 18,885 kg DW ha−1). The potato Yg ranged from 0.1 to 95.8% of the potential yield (x¯ = 42.1%, x~ = 46.0%, σx = 28.14% and CV = 0.67), hence there is an important difference that needs to be reduced. The classification tree analysis showed that inorganic N is the main yield explaining factor. While large yield gaps (Fourth quantile) are induced by low Inorganic N (< 88 kg ha−1) and scarce Human Labour energy (< 4196 MJ ha−1), small yield gap (First quantile) is mainly attributed to high N-inputs (≥ 139 kg ha−1 inorganic and ≥ 154 kg ha−1 organic). Third and Second quantiles (mid potato yield gaps) were characterized by more intricate nutrient input use, being difficult to classify; the Third quantile was partially explained by Inorganic N (< 139 kg ha−1), while part of the Second quantile by Extractable soil phosphorus (< 7.3 mg kg−1) and Inorganic N (< 139 kg ha−1). This classification can be helpful to diagnose the main site-specific crop management and biophysical recommendations towards closing the potato yield gap. The analysis suggests that there is opportunity to enhance potato actual yields in the study zone. More rational amount of inputs together with best management practices might improve potato productivities. However, sustainable potato intensification should be complemented with the expected quantification of environmental burdens under the local socio-economic constraints.status: Published onlin

Quantitative genetic analysis and comparison of physical and sensory descriptors relating to fruit flesh firmness in apple (Malus pumila Mill.)

Texture is a major component of consumer preference for eating-quality in apple. A quantitative genetic analysis of traits associated with fruit-flesh firmness was carried out. This was based on segregation in an unselected mapping population replicated at six sites and harvested over 2 years. Different methods of assessment were compared, and a principal components analysis carried out. Instrumental measures used were Magness-Taylor penetrometer readings, stiffness by acoustic resonance, and a range of sensory descriptors assessed by a trained panel. There were good correlations between some measures, although stiffness was poorly correlated. Whilst genotype by environment effects were large, significant effects were attributable to the genotype, and these were used to detect QTLs. Significant QTLs were detected on seven linkage groups, with large effects on linkage groups L01, L10 and L16. Whilst there was a poor correlation between acoustic stiffness and other measures, the significant and suggestive QTL detected for stiffness on linkage group L10 did represent a subset of significant QTLs detected for the penetrometer measure. The use of sensory assessment proved valuable in detecting QTLs representing different attributes of fruit texture. The possibility of interaction between significant QTLs for fruit texture and other strongly selected traits such as scab resistance and fruit acidity is addressed

Mitogen-Activated Protein Kinase Cross-Talk Interaction Modulates the Production of Melanins in Aspergillus fumigatus

Aspergillus fumigatus is the most important airborne human pathogenic fungus, causing thousands of deaths per year. Its lethality is due to late and often inaccurate diagnosis and the lack of efficient therapeutics. The failure of efficient prophylaxis and therapy is based on the ability of this pathogen to activate numerous salvage pathways that are capable of overcoming the different drug-derived stresses. A major role in the protection of A. fumigatus is played by melanins. Melanins are cell wall-associated macromolecules classified as virulence determinants. The understanding of the various signaling pathways acting in this organism can be used to elucidate the mechanism beyond melanin production and help to identify ideal drug targets. </jats:p